At the U.S. Agency for International Development, we are committed to a data-driven and evidence-based approach to development. Data plays a critical role in understanding our development impact, adapting our strategies, and communicating our results. But with limited time, resources, and technology, the process of identifying and collecting the right data — and making sure that data that is accurate, relevant, and useful — can be extremely challenging.
This data not only helps us better understand how businesses, governments, and nonprofits are collaborating to solve development challenges and allows for additional analysis and insights into partnerships and trends, but the process of collecting and sharing this information also demonstrates how far we have come and how far we still must go to effectively harness and utilize our data.
Data collection — although not a glamorous undertaking — is critical to being a data-driven organization. Through thoughtful reflection on the challenges of effective data collection and dissemination, we can enhance our ability to be evidence- and data-driven development practitioners, building on our successes and learning from our failures to ensure greater and more lasting impact from our programs.
Small data, good data
Small data can be a big undertaking, especially if you want to get it right. In the era of big data and tech startups, small data — those that can be processed using traditional database tools — can be seen as just that: small. Yet collecting up to 87 data points on each of the more than 360 active partnerships from 70 USAID missions, bureaus, and operating units is no small task.
An efficient data collection process takes several iterations and substantial collaboration to get right. In order to build a robust and accurate data set in a highly decentralized organization such as USAID, it is essential to know not only who has the information needed, but also on what kinds of platforms the information exists.
Collecting our partnership data also requires an understanding of the questions we want to answer; coordinating with other data collectors; identifying staff across the agency to help collect, process and review data; and developing methods to share the data with the world.
We have learned that good data requires thoughtfulness in the design of the process and a careful consideration of what development indicators to collect — both of which USAID continues to improve upon for PPPs. Good data also requires commitment as well as early and frequent engagement from a diverse group of internal and external partners and stakeholders. Suddenly small data stops looking so small.
Good data requires communication. The playwright George Bernard Shaw once said, "The single biggest problem in communication is the illusion it has taken place.” That observation extends to the data collection process.
Even if explicit written instructions are provided about the data being collected, terms such as “private sector” can still be interpreted many different ways, particularly in a cross-cultural environment. When this happened during the process of collecting the partnership data, we picked up the phone and talked to our contacts in the field, clarifying discrepancies and learning more about our colleagues’ work in the process.
A beginning of a dialogue
Data can unlock more questions than it answers. Over the years, as we have collected and analyzed our data, we also learned about the breadth of USAID’s partnership approaches and models. At partnerships.usaid.gov, you can search more than 1,600 partnerships dating back to 2001 by region, country or sector.
Yet, instead of seeing this information as an answer, we see it as the necessary first step to begin tackling more complex questions: What effects do different partnership models have on development impact? How does the state of a partner relationship relate to the results a partnership delivers? In what context are partnerships most likely to achieve their goals?
Data is more than just numbers — it’s the beginning of a dialogue. For an organization to be data-driven, it is important that data be accessible rather than overwhelming. While some people enjoy manipulating spreadsheets, most are too busy to learn from information in this format. For example, to encourage the use of our PPP data, we summarized the data in visually appealing presentations for internal use and met with staff across the agency to provide tailored overviews on the “state of public-private partnerships” at USAID.
These efforts took time, but also stimulated thoughtful dialogue and conveyed that this data was valued. Rather than treating the data like an item on a to-do list, we treated it like a gift from our colleagues.
USAID’s PPP data has been critical to telling our story; it has been used in everything from congressional testimonies to research papers. We are also seeing increased demand for data internally to more effectively communicate the value of our work. Yet, resources for data collection and sharing efforts can be scarce and are still often relegated to the doldrum task of “getting the work done.” But data can and should be a central part of the way we work.
Most importantly, this is an ongoing, evolving process, requiring regular reflection. Data collection is just the first step; we must also use data to understand current environments and gather more targeted evidence to inform decisions. For example, USAID using this data set as a starting point to examine sustainable partnership models and to explore internal capacity-building for private sector engagement.
As a data-driven organization committed to leveraging data and evidence to drive decision-making, USAID strives to use this PPP data to reflect on our offerings and build an evidence base for better understanding how to enhance private sector engagement to achieve our development goals.
With potential to change the trajectory of crises, such as famines or the spread of diseases, the innovative use of data will drive a new era for global development. Throughout this monthlong Data Driven discussion, Devex and partners — the Agence Française de Développement, BroadReach, Chemonics and Johnson & Johnson — will explore how the data revolution is changing our approach to achieving development outcomes and reshaping the future of our industry. Help us drive the conversation forward by tagging #DataDriven and @devex.
As a research and data associate with the Center for Transformational Partnerships in USAID’s Global Development Lab, through Dexis Consulting Group, Winnette performs research and data analysis on the agency’s public-private partnerships. She also conducts research on social entrepreneurship and other innovative approaches to private-sector engagement as a tool to advance development efforts globally. She is a recent graduate of Emory University’s master’s in development practice program, with concentrations in rights, ethics and governance.
Lisa Liu is a program analyst with the U.S. Global Development Lab’s Center for Transformational Partnerships. In this role, she performs research and data analysis on public-private partnerships and other approaches to private-sector engagement; she also develops tools to enable Agency staff to work in this area. Prior to joining USAID, Lisa worked a monitoring and evaluation firm, specializing in education and workforce development.
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